Moving object wireless posture monitoring system

Abstract

The invention provides a moving object wireless posture monitoring system. The system comprises a power source module, an inertia sensor module, a single-chip-microcomputer module, a wireless communication module and a remote display module. The signal output end of the inertia sensor module is connected with the single-chip-microcomputer module, the single-chip-microcomputer module outputs processed data to the remote display module through the wireless communication module, and posture angle information of the system is directly displayed on a remote terminal. The roll angle, the pitch angle and the yaw angle of the system can be displayed at the same time, so a user can monitor moving conditions of the system in real time and adjust an operation scheme. The system can be used for remote wireless dynamic monitoring of the inclination angle of the system, and has the advantages of achieving continuous monitoring, quick data acquisition and real-time display, being high in precision and the like.

Description

technical field [0001] The invention relates to the field of sensor data fusion, in particular to a wireless attitude monitoring system for moving objects. Background technique [0002] The accelerometer is used to measure the acceleration of the system and has high accuracy and fast response speed. The gyroscope measures the angular rate of the moving object, but there is a certain zero point drift, which is easy to cause a large error accumulation when performing angle integration , and the sensor information fusion technology with the Kalman filter algorithm as the core can perform complementary operations on the outputs of the two sensors. This not only takes advantage of the mutual cooperative operation of the two sensors, but also comprehensively processes the data of the information source to improve the intelligence of the entire sensor system and improve the measurement accuracy. In this process, the Kalman filter algorithm can effectively overcome the influence of...

AI Technical Summary

Problems solved by technology

Su Fei et al. from Fudan University studied the inertial sensing system for sail attitude information measurement in "Journal of Terahertz Science and Electronic Information", 2014(2): 183-189. By using the improved weighted Kalman filter The algorithm performs sensor data fusion to obtain the motion attitude information of the sail, and the accuracy reaches 1°, but the system cannot perform remote monitoring

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